Table of content:
Platform as a service (PaaS) is one of the 3 main cloud type services. The other two are Infrastructure as a service (IaaS) and Software as a service (SaaS). PaaS is the second step in Cloud services. It provides all of the things IaaS does, plus all you need to develop and deploy your software, middleware and every service needed for data analysis and management. PaaS is the perfect way to streamline your developing process and optimize the time from idea to market. With a robust framework provided by the PaaS your team can use already tested and working solutions for some of the common design and integration problems without the need to reinvent the wheel every time. This will help them concentrate on the new thing your app/program will provide.
Zimki is considered to be the first platform as a service provider. It was owned by a company named Fotango. The company started in the Photography industry. After you register on the site you would request a prepaid envelope and then send them a photography film roll. They will develop it, scan it, print the photos for you and send them to you. But the difference from other companies was they would save these photos on their servers and allow you to see them from anywhere and even share them. In 2000 Canon was looking to expand their online presence and they decided to buy them. By 2002 the deal was finished.
By 2007 Zimiki was doing very well, but some of their clients feared vendor lock-in and this sentiment was growing. So they decided to address this by going open source. In this way they would encourage other IaaS providers to add Zimiki`s platform and their clients can switch hosting providers, if they don’t feel the current one is good enough. Zimiki and Fotango will act as central authority about everything Zimiki and will provide IaaS to everyone who wishes to use it. The problem was that their parent company Canon did not approve this and they decided to close it.
As you will see a bit later from the top providers the future of PaaS as is today is not very certain. Most of the providers bundle their PaaS with IaaS and SaaS. And by large they are so much integrated with other services provided by them it is hard to distinguish them anymore. In that regard PaaS looks more like “serverless” with every passing day. This in some cases is heralded like evolution and branded by PR with some new letter in front of PaaS like for example xPaaS or whatever the marketing department can think of. So people are turning more and more to container base models like Kubernetes to avoid Lock-ins.
They are not ordered by any particular order.
IBM Cloud – IBM Cloud Foundry is PaaS that allows you to use Java, Node, Php, Python, Ruby, Swift and Go apps. With their projects like Diego, Garden and Eirini you can use standard applications and container based applications at the same time without the need to swap infrastructure or to worry about integration.
IBM offers are not just limited to PaaS . They offer a wide range of services that help you in every possible scenario. Because services are developed for IBM, integration of one service with another is easy.
It does not matter if you want a virtual AI assistant (IBM Watson) or you want to automate your production to help you with improving your performance with AI (IBM Cloud Pak) you can find it here.
Microsoft offers a very good SDK which can be integrated with Visual Studio so you don’t even need to change the way you work to be able to take advantage of them. Combine that with 200 + data centers they have and you have a very good and easy distribution network, that is easy to scale and close to your customers.
Microsoft also offers Virtualized machines, Azure App Service, Azure Kubernetes Services and more than 200 other services. If you are worried about longevity and support, well it is Microsoft, chances are you are reading this on a Windows powered computer who can support old printers.
AWS Elastic Beanstalk is Amazon’s version of PaaS. Given that they are the biggest Cloud infrastructure provider in the world right now you can be sure it works and it works well.Build of their own need to scale and the need to reduce operational cost, you know they build a very robust and efficient system.
As with most of the entries in here you can upload applications programmed using Java, .NET, PHP, Node.js, Python, Ruby, Go. AWS also boasts that you can retain full control of the resources allocated to you through Elastic Beanstalk’s management if you don’t like the way they scale.
This is Google’s response. As any other provider you can see they have integrated all of their services and made them available to you through easy access to API-s or one click installs. Here you can run your own runtime environment using Dockerfile or run them in the standard environment for the language you use.
The one big advantage they have is, it all runs on google infrastructure. And the last time that failed it was reported on my national news channel.
As everything PaaS is evolving and changing. The fierce competition in this multi billion business will push the innovation forward and force the top players to strive to offer you everything that their competitors have, but with something else from them that makes them stand out from the crowd. That is a good thing because then the choice is left to personal preference [ and price 🙂 ]. It will be interesting to follow this evolution and possibly write another article about the changes in a few years.
We can provide you with robust, reliable and affordable infrastructure on which you can deploy your open PaaS. We offer dedicated servers that can handle heavy sustained loads over prolonged time without throttling, and with our control panel you can add more servers at any time, if the current configuration can’t handle the required load.
If you are new to machine learning you probably are wondering “What hardware specifications does my computer or server need to run machine learning?”. We have combined the results of the tests run by pugetsystems and came with the short answer short answer “With a lot of GPUs and VRam”, the longer and more detailed answer can be read a bit late in that article (link to chapter), but to be useful to as many people as possible we will start with some basic information about machine learning.
Most of the people who work with 3D have asked themselves how can I speed the rendering process. And all of them have some advice to give. But it is mostly set this setting to 3 instead of 4, and this one to 13 instead of 25.